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Journal of Infection and Public Health 10 (2017) 548–563

Contents lists available at ScienceDirect

Journal of Infection and Public Health

j o u r n a l h o m e p a g e : h t t p : / / w w w . e l s e v i e r . c o m / l o c a t e / j i p h

uestionnaire-based analysis of infection prevention and control in ealthcare facilities in Saudi Arabia in regards to Middle East espiratory Syndrome

li A. Rabaan a,∗, Hatem M. Alhani b,c, Ali M. Bazzi d, Shamsah H. Al-Ahmed e

Molecular Diagnostic Laboratory, Johns Hopkins Aramco Healthcare, Dhahran, Saudi Arabia Specialty Paediatric Medicine, Maternity and Children Hospital, Dammam, Saudi Arabia Directorate of Infection Control at Eastern Province, Ministry of Health, Dammam, Saudi Arabia, Microbiology Laboratory, Johns Hopkins Aramco Healthcare, Dhahran, Saudi Arabia Specialty Paediatric Medicine, Qatif Central Hospital, Ministry of Health, Qatif, Saudi Arabia

r t i c l e i n f o

rticle history: eceived 2 July 2016 eceived in revised form 24 October 2016 ccepted 18 November 2016

eywords: audi Arabia nfection prevention nfection control ealthcare workers ERS-CoV

a b s t r a c t

Effective implementation of infection prevention and control in healthcare facilities depends on training, awareness and compliance of healthcare workers. In Saudi Arabia recent significant hospital outbreaks, including Middle East Respiratory Syndrome Coronavirus (MERS-CoV), have resulted from lack of, or breakdown in, infection prevention and control procedures. This study was designed to assess attitudes to, and awareness of, infection prevention and control policies and guidelines among healthcare workers of different professions and institution types in Saudi Arabia. A questionnaire was administered to 607 healthcare workers including physicians (n = 133), nurses (n = 162), laboratory staff (n = 233) and other staff (n = 79) in government hospitals, private hospitals and poly clinics. Results were compared using Chi square analysis according to profession type, institution type, age group and nationality (Saudi or non- Saudi) to assess variability. Responses suggested that there are relatively high levels of uncertainty among healthcare workers across a range of infection prevention and control issues, including institution-specific issues, surveillance and reporting standards, and readiness and competence to implement policies and respond to outbreaks. There was evidence to suggest that staff in private hospitals and nurses were more confident than other staff types. Carelessness of healthcare workers was the top-cited factor contributing to causes of outbreaks (65.07% of total group), and hospital infrastructure and design was the top-cited factor contributing to spread of infection in the hospital (54.20%), followed closely by lack and shortage of

staff (53.71%) and no infection control training program (51.73%). An electronic surveillance system was considered the most effective by staff (81.22%). We have identified areas of concern among healthcare workers in Saudi Arabia on infection prevention and control which vary between institutions and among different professions. This merits urgent multi-factorial actions to try to ensure outbreaks such as MERS- CoV can be minimized and contained.

© 2017 The Authors. Published by Elsevier Limited. This is an open access article under the CC

ntroduction

Effective infection prevention and control in healthcare facili- ies depends on awareness and compliance of healthcare workers HCWs) at all levels of the organization. Thus, as for all health pol-

∗ Corresponding author at: P.O. Box 76, Room 281-C, Building 62, Johns opkins Aramco Healthcare, Saudi Aramco, Dhahran 31311, Saudi Arabia. ax: +966 13 877 6741.

E-mail addresses: [email protected], [email protected] (A.A. Rabaan), [email protected] (H.M. Alhani), [email protected] (A.M. Bazzi), [email protected] (S.H. Al-Ahmed).

ttp://dx.doi.org/10.1016/j.jiph.2016.11.008 876-0341/© 2017 The Authors. Published by Elsevier Limited. This is an open access ar d/4.0/).

BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

icy, multi-disciplinary teams involving staff from frontline workers to management should be involved in formulation and implemen- tation of infection prevention and control policies and procedures to ensure that they function effectively [1].

In the case of Saudi Arabia, as in any other country, there are spe- cific challenges to infection prevention and control which need to be met by nationally and locally relevant policies and procedures. Various nosocomial and community infectious disease outbreaks have been experienced in Saudi Arabia in recent years. These

include pandemic influenza A (H1N1) [2], H5N1 highly pathogenic avian influenza [3], Rift Valley Fever [4] and most significantly Mid- dle East Respiratory Syndrome (MERS), an acute viral respiratory

ticle under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-

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A.A. Rabaan et al. / Journal of Infect

llness associated with high mortality, caused by a new betacoron- virus strain, MERS-CoV [5–8].

MERS-CoV was first positively identified in 2012 in the sputum f a 60-year old man, who died after presenting at a private hos- ital in Jeddah with acute pneumonia and subsequent renal failure 8]. Human MERS-CoV is believed to have originated via cross-over rom dromedary camels, but the major outbreaks experienced in he Middle East and Korea have been healthcare facility–associated nd linked to a lack of, or breakdown in, infection prevention and ontrol procedures [5,6,9–12]. As a result, the World Health Orga- ization (WHO) have identified issues such as overcrowding in mergency department waiting rooms and insufficient attention to asic infection control procedures, such as hand hygiene and use of ersonal protective equipment (PPE), in hospitals in Saudi Arabia 11]. New infection prevention and control guidelines for MERS- oV patients were introduced by the Ministry for Health (MOH) in audi Arabia, largely based on WHO and Centers for Disease Control nd Prevention (CDC) guidelines, with modifications based on epi- emiological evidence, clinical experience and local circumstances 6,13–16].

The effectiveness of promotion and consistent application of oth basic infection control procedures such as hand hygiene, and ore advanced measures, have been demonstrated in hospital-

ssociated MERS-CoV outbreaks in Saudi Arabia and in Korea 17–20]. However, in order for MOH-prescribed infection pre- ention and control measures to be effectively implemented n individual healthcare facilities and their constituent depart-

ents, clear direction must be given to employees. Expectations f both management and employees should be clearly defined, ommunicated and understood [1,7]. The objective of this uestionnaire-based study was to gauge staff awareness of infec- ion prevention and control policies and procedures in different ealthcare facilities in Saudi Arabia, including government hos- itals, private hospitals and poly clinics. The questionnaires were ompleted by a range of HCWs, including nurses, physicians, lab- ratory staff and others such as physiotherapists. They addressed taff training and access to information, confidence in the ability of CWs to implement policies and carry out procedures, their assess- ent of the main threats in terms of possible outbreak causes and

actors contributing to infection spread, and preparedness of their nstitution to deal with an infection outbreak.

aterial and methods

ubjects and questionnaires

607 HCWs including physicians (n = 133), nurses (n = 162), lab- ratory staff (n = 233) and other staff (n = 79), in government ospitals, private hospitals and poly clinics in Saudi Arabia filled

n a questionnaire. The questionnaire was administered via Sur- eyMonkey and distributed to HCWs through emails, Facebook, nd other communication tools. Responses were anonymous and he institutions where respondents were working were not iden- ified by name. Hence, it was not considered necessary to seek thical approval. The questionnaire included a range of thirteen uestions on their knowledge and application of, and attitudes to,

nfection prevention and control measures in their institutions. The uestionnaire administered is shown in Appendix A. For aid of

nterpretation, the questions have been numbered as follows for onsideration in the Results and Discussion Sections of this paper.

Question 1:

(a) Do you have infection control program at your institution? b) Do you have infection control policies and guidelines in your

unit?

d Public Health 10 (2017) 548–563 549

Question 2: Have you received some form of training or orien- tation about infection prevention and control?

Question 3: At your institution, do you have active infection control team?

Question 4: Do you have an emerging infectious diseases task force (dealing with outbreaks)?

Question 5: Have you encountered any outbreak? Question 6: Is your hospital is enrolled in national surveillance

system? Question 7: Do you have a list of reportable infectious agents

available in your unit and accessible to all staff? Question 8: Which infections are reported to MOH? Question 9: In your institution, is there known turnaround time

of laboratory results of the reportable infectious agents? Question 10: Do you think your hospital is prepared for any

infection outbreak? Question 11: Do you agree that surveillance tool used in your

institution is effective to prevent or control infection? Question 12: Do you think that all staff in your unit are following

promptly infection control policies, rules and guidelines? Question 13: Do you think that all staff can differentiate between

different isolation protocol such as droplet or contact? The group were also asked to choose from a number of options

as to what, in their opinion, was the cause(s) of outbreaks and what factors contribute to the spread of infection in the hospital? They were also asked what reporting system they had in their hospitals (Electronic surveillance, paper version or telephone communica- tion) and which of these systems they would consider to be the most effective reporting system for reporting infectious agents.

Statistics

Data were analyzed statistically using Excel (Microsoft Corpo- ration, Redmond, WA, USA) and/or Social Science Statistics (http:// www.socscistatistics.com/Default.aspx). The chi-square test was used at the 5% level of significance to estimate differences in propor- tions between different staff types (physicians, nurses, laboratory staff and others), between staff in different institution types (gov- ernment hospital, private hospital and poly clinic), between staff of different age groups, or between Saudi and non-Saudi staff. Where appropriate, median and interquartile range (IQR) were also calcu- lated (staff type analyses).

Results

Characteristics of study group

A total of 607 HCWs, comprising physicians, nurses, labora- tory staff and others (for example physiotherapists, respiratory technicians, X-ray technicians), working between government hos- pitals, private hospitals and poly clinics, submitted responses to the questions shown in Section “Subjects and questionnaires”. The characteristics of the group in terms of age group, gender, profes- sion, institution and nationality (Saudi or non-Saudi) are shown in Table 1.

Responses by profession

The responses to the questions asked were compared between the different HCW professions across the three institution types. Numbers and percentages of responses in each group and the p values obtained from Chi square analyses are shown in Table 2. The

Chi square breakdowns are shown in Appendix B.

There was some variation in responses to questions related to institution-specific issues (Questions 1–5, Section “Subjects and questionnaires”). In terms of knowledge of whether or not there

550 A.A. Rabaan et al. / Journal of Infection an

Table 1 Characteristics of subjects.

Age (y) Number (total 607)

18–29 179 30–44 305 45–59 112 >60 11

Gender Male 269 Female 338

Profession Physician 133 Nurse 162 Laboratory staff 233 Others 79

Institution Private hospital 119 Government hospital 452 Poly clinic (private sector) 36

Nationality

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Saudi 446 Non-Saudi 161

s an infection control program at their institution (Question 1a), here was no significant difference noted across the groups (Chi quare 10.331; p = 0.111379; Table 2, Appendix B). However, there as significant variation in responses on whether there is an infec-

ion control program in their unit (Question 1b; Chi square 20.526; = 0.00223). This was mainly attributable to disparity in the ‘don’t now’ response levels (Table 2, Appendix B). The highest percent- ge of uncertainty was among ‘others’ (13.92% don’t know), while he lowest level of uncertainty was expressed by nurses (2.47%).

There was also significant variation in response to the question oncerning receipt of training/orientation on infection prevention nd control (Question 2; Chi square 15.9627, p = 0.001154; Table 2, ppendix B). Nurses were the group least likely to have received no

raining (12.35%) (Table 2). Overall, 23.06% of participants reported aving received no training (Table 2, Appendix B).

There were significantly different levels of awareness between ifferent HCW professions regarding implementation of infection revention and control policy. On there was an active infection ontrol team at the institution, there was significant variation Question 3; Chi square 13.708, p = 0.03307). Physicians were 1.67 imes more likely than nurses to state that there was no infection ontrol team, while the level of uncertainty reflected in ‘don’t know’ nswers was similar between these two groups (Table 2, Appendix ). Meanwhile, the laboratory staff and ‘others’ groups had a higher

evel of uncertainty than either the physicians or nurses (‘don’t now’ percentages). However, on the related point of whether the nstitution had an emerging infectious diseases task force (dealing

ith outbreaks) (Question 4), there was no significant difference cross the groups. On this question, there was a high level of uncer- ainty across the whole cohort (32.13% ‘don’t know’) and within ll individual subgroups. On the question of whether an outbreak ad ever been encountered in their institution, there was again ignificant variation (Question 5; Chi square 18.531, p = 0.00503), argely accounted for by the significantly lower levels of uncertainty xpressed by physicians as compared to the other groups (‘don’t now’ responses, Table 2, Appendix B), and the fact that the labo- atory staff were the only group more likely to state there had not een an outbreak, rather than that there had been an outbreak.

On questions on surveillance and reporting standards (ques-

ions 6–9, Section “Subjects and questionnaires”), there were also lements of variation. There was no significant variation on the uestion of whether their hospital is enrolled in the national urveillance system (Question 6; Chi square 8.015; p = 0.237;

d Public Health 10 (2017) 548–563

Table 2, Appendix B). On this question, there were uniformly high levels of uncertainty across the groups, with an overall level of ‘don’t know’ answers of 35.09% (Table 2). By contrast, on the ques- tion of whether there was a list of reportable infectious agents available in their unit and accessible to all staff (Question 7), there was significant variation (Table 2; Chi square 23.58; p = 0.000624; Table 2, Appendix B). This was largely due to the higher than expected levels of nurses reporting positively compared to other groups. It was also attributable to the high levels of uncertainty (don’t know percentages) of both laboratory and other staff com- pared to both physicians and nurses (Table 2, Appendix B). Overall, only 46.95% of participants reported that there is an accessible list in their unit (Table 2). On the related question of which infections are reported to the MOH (Question 8), there was again significant variation in responses (Chi square 19.7608; p = 0.00305; Table 2, Appendix B). This was mainly attributable to higher than expected numbers of nurses responding that all infections were reported and lower than expected levels of ‘don’t know’ answers for nurses compared to the other groups, and to higher than expected lev- els of uncertainty among lab staff (Table 2, Appendix B). On the question of whether their institution had a known turnaround time of laboratory results for reportable infectious agents (Question 9), there was a substantial level of uncertainty among staff, with overall ‘don’t know’ responses of 28.99% (Table 2). There was signif- icant variation across the groups (Chi square 34.373; p = 0.0000057; Table 2, Appendix B). This was mainly attributable to the signifi- cantly lower than expected levels of ‘don’t know’ responses among laboratory staff and the higher than expected levels for the other groups (Table 2, Appendix B).

On questions relating to readiness and competence of the institution and staff (Questions 10–13, Section “Subjects and ques- tionnaires”), there was again a level of variation between staff types. On the question of whether their hospital is prepared for any infection outbreak, there were significant differences of opin- ion (Question 10; Chi square 26.74; p = 0.000162; Table 2, Appendix B). In particular, while the majority of nurses (58.64%) thought their hospital was prepared for an outbreak, only 37.60% of physicians agreed. Overall, only 48.76% of total staff thought their hospital was prepared for an outbreak (Table 2, Appendix B). On the ques- tion of whether the surveillance tool used in their institution is effective to prevent or control infection (Question 11) there was no significant variation (Chi square 9.955; p = 0.1265599; Table 2, Appendix B), with an overall ‘don’t know’ response level of 22.24%. On the question of whether all staff in their unit were following promptly infection control policies, rules and guidelines (Ques- tion 12), there was a high level of pessimism across the groups, with 54.01% of all staff responding negatively (Table 2). There was significant variation between the groups (Chi square 19.583; p = 0.00328437). This was mainly attributable to the substantially lower than expected numbers of physicians responding positively, and the lower than expected ‘don’t know’ responses of nurses and higher than expected ‘don’t know’ responses of physicians on this question (Table 2, Appendix B). On the related question of whether all staff can differentiate between different isolation protocols such as droplet or contact (Question 13), again there was significant vari- ation (Chi square 39.826; p = 4.9 × 10−7; Table 2, Appendix B). This was mainly attributable to the higher than expected number of ‘yes’ responses and lower number of ‘no’ responses from nurses and to the opposite trend for physicians (Table 2, Appendix B). Addition- ally, both the lab and ‘others’ staff had higher than expected levels of ‘don’t know’ responses, while nurses had lower than expected levels. Overall, only 31.96% of total staff agreed that all staff can

differentiate between different isolation protocols such as droplet or contact (Table 2).

A.A. Rabaan et al. / Journal of Infection and Public Health 10 (2017) 548–563 551

Table 2 Distribution of responses according to profession.

Question Response All staff (N = 607) Physicians (N = 133) Nurses (N = 162) Lab staff (N = 233) Others (N = 79) p

Number/percentage of group

Question 1a Y 500/82.37 116/87.22 136/83.95 191/81.97 57/72.15 0.111379 N 55/9.06 8/6.02 15/9.26 23/9.87 9/11.39 DK 52/8.57 9/6.77 11/6.79 19/8.15 13/16.46

Question 1b Y 486/80.07 99/74.44 142/87.65 191/81.97 54/68.35 0.00223 N 82/13.51 21/15.79 16/9.88 31/13.30 14/17.72 DK 39/6.43 13/9.77 4/2.47 11/4.72 11/13.92

Question 2 Y 467/76.94 102/76.69 142/87.65 165/70.82 58/73.42 0.001154 N 140/23.06 31/23.31 20/12.35 68/29.18 21/26.58

Question 3 Y 389/64.09 77/57.89 116/71.60 143/61.37 53/67.09 0.03307 N 144/23.72 43/32.33 31/19.36 57/24.46 13/16.46 DK 74/12.19 13/9.77 15/9.26 33/14.16 13/16.46

Question 4 Y 242/39.87 49/36.84 73/45.06 87/37.34 33/41.77 0.6109 N 170/28.01 42/31.58 44/27.16 63/27.04 21/26.58 DK 195/32.13 42/31.58 45/27.78 83/35.62 25/31.65

Question 5 Y 272/44.81 70/52.63 82/50.62 84/36.05 36/45.57 0.00503 N 218/35.91 48/36.09 46/28.40 99/42.49 25/31.65 DK 117/19.28 15/11.28 34/20.99 50/21.46 18/22.78

Question 6 Y 269/44.15 60/45.11 84/51.23 89/38.30 36/45.57 0.2370 N 125/20.76 26/19.55 27/17.28 54/23.18 18/22.78 DK 213/35.09 47/35.34 51/31.48 90/38.63 25/31.65

Question 7 Y 285/46.95 60/45.11 96/59.26 93/39.91 36/45.57 0.000624 N 206/33.94 55/41.35 45/27.78 84/36.05 22/27.85 DK 116/19.11 18/13.53 21/12.96 56/24.03 21/26.58

Question 8 Healthcare associated 129/21.25 25/18.80 38/23.46 50/21.46 16/20.25 0.00305 All 282/46.46 60/45.11 92/56.79 91/39.06 39/49.37 DK 196/32.29 48/36.09 32/19.75 92/39.48 24/30.38

Question 9 Y 313/51.57 50/37.59 82/50.62 146/62.66 35/44.30 0.0000057 N 118/19.44 30/22.56 27/16.67 48/20.60 13/16.46 DK 176/28.99 53/39.85 53/32.72 39/16.74 31/39.24

Question 10 Y 296/48.76 50/37.60 95/58.64 107/45.92 44/55.70 0.000162 N 217/35.75 62/46.62 56/34.57 79/33.91 20/25.32 DK 94/15.49 21/15.79 11/6.79 47/20.17 15/18.94

Question 11 Y 316/52.06 54/40.60 91/56.17 128/54.94 43/54.43 0.1265599 N 156/25.70 43/32.22 37/22.84 59/25.32 17/21.52 DK 135/22.24 36/27.07 34/20.99 46/19.74 19/24.05

Question 12 Y 196/32.29 28/21.05 55/33.95 82/35.91 31/39.24 0.00328437 N 329/54.01 79/59.40 95/58.64 121/51.93 34/43.04 DK 82/13.51 26/19.55 12/7.41 30/12.88 14/17.73

Question 13 Y 194/31.96 28/21.05 77/47.53 64/27.47 25/31.65 4.9 × 10−7 N 314/51.73 88/66.17 69/42.59 124/53.22 33/41.77

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DK 99/16.31 17/12.78

: yes; N: no; DK: don’t know; p < 0.05 considered significant (from Chi square com

esponses by institution

The responses to the questions asked were also compared etween the different institution types (Table 1) to determine if here was any variation. Numbers and percentages of responses n each group and the p values obtained from Chi square analyses re shown in Table 3 and the Chi square breakdowns are shown in ppendix C.

There was variation in responses to questions related to nstitution-specific issues (Questions 1–5, Section “Subjects and uestionnaires”). In terms of knowledge of whether or not there

s an infection control program at their institution (Question 1a) or heir unit (Question 1b), there was significant variation (Chi square 7.6147, p = 0.000015 and Chi square 24.8587; p = 0.000054 respec- ively; Table 3, Appendix C). This was mainly attributable to the

esponses of the poly clinics staff, who had lower than expected evels of ‘yes’ responses, and higher than expected ‘no’ and ‘don’t now’ responses, compared to government or private hospitals

16/9.88 45/19.31 21/26.58

n).

(Table 3, Appendix C). In terms of whether staff had received some form of training or orientation about infection prevention and con- trol, there was also significant variation (Question 2; Chi square 7.0553; p = 0.029373; Table 3, Appendix C). This was mainly due to private hospital staff being less likely than expected to report no training in comparison to the other institution types (Table 3, Appendix C). There were also significantly different levels of aware- ness between staff at different institutions of whether there was an active infection control team (Question 3; Chi square 32.5774; p < 0.00001). This was mainly due to private hospital staff being more likely than expected to respond positively and less likely to respond negatively, while poly clinics staff were substantially less likely to respond positively (Table 3, Appendix C). As mentioned in Section “Responses by profession”, there was a high level of uncertainty across the whole group (32.13% ‘don’t know’) on the

related point of whether the institution had an emerging infectious diseases task force (dealing with outbreaks) (Question 4; Table 3, Appendix C). However, there was variation across the institution

552 A.A. Rabaan et al. / Journal of Infection and Public Health 10 (2017) 548–563

Table 3 Distribution of responses by institution.

Question Response All staff (n = 607) Government hospital (n = 452) Private hospital (n = 119) Poly clinic (n = 36) p Number/percentage of groups

Question 1a Y 500/82.37 373/82.52 108/90.76 19/52.78 0.000015 N 55/9.06 41/9.07 5/4.20 9/25.00 DK 52/8.57 38/8.41 6/5.04 8/22.22

Question 1b Y 486/80.07 350/77.43 113/87.65 23/63.89 0.000054 N 82/13.51 70/15.49 4/3.36 8/22.22 DK 39/6.43 32/7.08 2/1.68 5/13.89

Question 2 Y 467/76.94 340/75.22 102/85.71 25/69.44 0.029373 N 140/23.06 112/24.78 17/14.29 11/30.56

Question 3 Y 389/64.09 279/61.73 96/80.67 14/38.89 <0.00001 N 144/23.72 111/24.56 14/11.76 19/52.78 DK 74/12.19 62/13.72 9/7.56 3/8.33

Question 4 Y 242/39.87 166/36.73 64/53.78 12/33.33 0.012449 N 170/28.01 132/29.20 25/21.01 13/36.11 DK 195/32.13 154/34.07 30/25.21 11/30.56

Question 5 Y 272/44.81 205/45.35 55/46.22 12/33.33 0.087021 N 218/35.91 153/33.85 45/37.82 20/55.56 DK 117/19.28 94/20.80 19/15.97 4/11.11

Question 6 Y 269/44.15 190/42.04 66/55.46 13/36.11 0.061478 N 125/20.76 93/20.58 23/19.33 9/25.00 DK 213/35.09 169 37.39 30/25.21 14/38.89

Question 7 Y 285/46.95 204/45.13 66/55.46 15/41.67 0.171037 N 206/33.94 163/36.06 32/26.89 11/30.56 DK 116/19.11 85/18.81 21/17.64 10/27.78

Question 8 Healthcare associated 129/21.25 101/22.35 17/14.29 10/27.78 0.003537 All 282/46.46 198/43.81 73/61.34 11/30.56 DK 196/32.29 153/33.85 29/24.37 15/41.67

Question 9 Y 313/51.57 209/46.24 87/73.11 17/47.22 0.000011 N 118/19.44 95/21.02 14/11.76 9/25.00 DK 176/28.99 148/32.74 18/15.13 10/27.78

Question 10 Y 296/48.76 194/42.92 86/72.27 16/44.44 <0.00001 N 217/35.75 187/41.37 18/15.13 12/33.33 DK 94/15.49 71/15.71 15/12.61 8/22.22

Question 11 Y 316/52.06 227/50.22 73/61.34 16/44.44 0.15522 N 156/25.70 124/27.43 23/19.33 9/25.00 DK 135/22.24 101/22.35 23/19.33 11/30.56

Question 12 Y 196/32.29 131/28.98 51/42.86 14/38.89 0.001288 N 329/54.01 263/58.19 54/45.38 12/33.33 DK 82/13.51 58/12.83 14/11.76 10/27.78

Question 13 Y 194/31.96 134/29.65 48/40.34 12/33.33 0.215902 N 314/51.73 245/54.20 52/43.70 17/47.22

19/15.97 7/19.44

Y parison).

t v p b s

t e q s T f t s o s T w s

Table 4 Gender distribution of healthcare professions.

Profession Gender

Male (n = 269) Female (n = 338) N (expected) [Chi square] N (expected) [Chi square] % of males % of females

Physician 63 (58.94) [0.28] 70 (74.06) [0.22] 23.42 20.71

Nursing 26 (71.79) [29.21] 136 (90.21) [23.25] 9.67 40.24

Laboratory 135 (103.26) [9.76] 98 (129.74) [7.77] 50.19 28.99

DK 99/16.31 73/16.15

: yes; N: no; DK: don’t know; p < 0.05 considered significant (from Chi square com

ypes (Chi Square 12.7713; p = 0.012449), mainly due to the pri- ate hospitals staff being more likely than expected to respond ositively (Table 3, Appendix C). On the question of whether an out- reak had ever been encountered in their institution, there was no ignificant variation (Question 5; Chi square 8.1274; p = 0.087021).

On questions on surveillance and reporting standards (ques- ions 6–9, Section “Subjects and questionnaires”), there were also lements of variation. There was no significant variation on the uestion of whether their hospital is enrolled in the national urveillance system (Question 6; Chi square 8 8.9849; p = 0.061478; able 3, Appendix C). As mentioned in Section “Responses by pro- ession”, there were uniformly high levels of uncertainty across he groups on this question (Tables 2 and 3). There was also no ignificant variation on the question of whether there was a list f reportable infectious agents available in their unit and acces-

ible to all staff (Question 7; Chi square 6.4025; p = 0.171037; able 3, Appendix C). However with respect to the question of hich infections are reported to the MOH (Question 8), there was

ignificant variation (Chi square 15.6436; p = 0.003537; Table 3,

Others 45 (35.01) [2.85] 34 (43.99) [2.27] 16.73 10.06

Appendix C). This was mainly due to staff at private hospitals being

relatively more likely to respond that all infections are reported (Table 3, Appendix C). On the question of whether their institu- tion had a known turnaround time of laboratory results of the

ion an

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A.A. Rabaan et al. / Journal of Infect

eportable infectious agents (Question 9), there was significant ariation (Chi square 28.1901; p = 0.000011; Table 3, Appendix C). his was mainly accountable to differences of private hospital staff esponses compared to other institutions, as they were significantly ore likely to respond positively (Table 3, Appendix C). On questions relating to readiness and competence of the

nstitution and staff (Questions 10–13, Section “Subjects and uestionnaires”), there was again a level of variation between insti- utions. On the question of whether their hospital was prepared for ny infection outbreak, there were significant differences (Ques- ion 10; Chi square 36.7054; p < 0.00001; Table 3, Appendix C). This as again due to private hospital staff being significantly more

ikely to respond positively and less likely to respond negatively han expected (Table 3, Appendix C). On whether the surveillance ool used in their institution is effective to prevent or control infec- ion (Question 11) there was no significant variation (Chi square 9 .656; p = 0.15522; Table 3, Appendix C), with uniformly high lev- ls of uncertainty across the groups (Table 3). On the question of hether all staff in their unit were following promptly infection

ontrol policies, rules and guidelines (Question 12), there was a igh level of pessimism across the groups, as mentioned in Section Responses by profession” (Tables 2 and 3). There was significant ariation between the groups (Chi square 17.9049; p = 0.001288), ainly due to the higher than expected numbers of private hospital

taff who responded positively (Table 3, Appendix C). On the related uestion of whether all staff can differentiate between different iso-

ation protocols such as droplet or contact (Question 13), however, here was no significant variation between institution types (Chi quare 5.7836; P = 0.215902; Table 3, Appendix C).

ender, age group and nationality

Distribution of males and females across the different HCW rofessions varied significantly (Chi square 75.6004; p < 0.00001; able 4). In particular, nurses were significantly less likely to be ales and significantly more likely to be females than expected, hile both lab and other staff were more likely than expected to be ales (Table 4). As distribution of answers to some of the questions

aried according to profession, and there was a difference in the

ender balance across the four professions included, we checked f there was also any impact of gender on responses. However, esponse distributions for males and females were generally both ery similar to those for the group as a whole (data not shown).

able 5 ge group distribution of healthcare professions and institution types.

Age group (y)

18–29 (n = 179) 30–44 (n = 305) N (expected) [Chi square] N (expected) [Ch % of age group % of age group

Profession Physician 27 (39.22) [3.81] 53 (66.83) [2.86]

15.1 17.4 Nursing 62 (47.77) [4.24] 85 (81.40) [0.16]

34.6 27.9 Laboratory 63 (68.71) [0.47] 130 (117.08) [1.4

35.2 42.6 Others 27 (23.30) [0.59] 37 (39.70) [0.18]

15.1 12.1

Institution Government hospital 125 (133.29) [0.52] 245 (227.12) [1.4

69.9 80.3 Private hospital 43 (35.09) [1.78] 40 (59.79) [6.55]

24 13.1 Poly clinic 11 (10.62) [0.01] 20 (18.09) [0.20]

6.1 6.6

d Public Health 10 (2017) 548–563 553

We also considered whether there might be variation in pro- fession type or institution type, and/or in responses to questions, according to age group of participants. Distribution of HCW pro- fession varied significantly according to age group (Chi-square 50.3116; p < 0.00001). This was mainly attributable to a higher than expected number of nurses falling in the 18–29 year age group, and fewer than expected in the 45–59 year age group, while the opposite was the case for physicians (Table 5). Also, there was some variation in distribution of age groups of participants with respect to institution type (Chi-square 22.8911; p = 0.000834). This was mainly attributable to higher than expected numbers of par- ticipants in the 18–19 and 45–59 year age groups, and lower than expected numbers of participants in the 30–44 year age group, working in private hospitals (Table 5).

We also considered whether there might be a variation in responses to the questionnaire among staff of different age groups (Table 6, Appendix D). In terms of institution-specific questions 1–5, there was significant variation with age group in response to question 1A (whether or not there is an infection control program at their institution; Chi-square 19.2662; p = 0.003737), question 3 (whether there is an active infection control team in their insti- tution; Chi square 21.3123; p = 0.001612), question 4 (whether the institution had an emerging infectious diseases task force; Chi square 22.4748; p = 0.000993) and question 5 (whether an outbreak had ever been encountered in their institution; Chi square 19.018; p = 0.004133). In each case, the variation was mainly attributable an age-dependent decrease in levels of uncertainty (don’t know answers). Staff in the 18–29 years category tended to have higher than expected levels of ‘don’t know’ answers to these questions, while respondents in the 45–59 year category had lower than expected levels of ‘don’t know’ responses (Table 6, Appendix D). There was no apparent age-dependent effect on the likelihood of staff having received training (Question 2; Chi-square 1.2854; p = 0.732612) or on their awareness of whether there is an infec- tion control program in their unit (Question 1b; Chi-square 7.7791; p = 0.254737).

On questions on surveillance and reporting standards (questions 6–9, Section “Subjects and questionnaires”), there was significant variation with age group for every question (Table 6, Appendix D). Once again, the variation was mainly attributable to higher

than expected levels of ‘don’t know’ answers among the 18–29 years category, while again respondents in the 45–59 year category had lower than expected levels of ‘don’t know’ responses (Table 6, Appendix D).

45–59 (n = 112) ≥60 (n = 11) i square] N (expected) [Chi square] N (expected) [Chi square]

% of age group % of age group

49 (24.54) [24.38] 4 (2.41) [1.05] 43.8 36.4

13 (29.89) [9.55] 2 (2.94) [0.30] 11.6 18.2

3] 36 (42.99) [1.14] 4 (4.22) [0.01] 32.1 36.4

14 (14.58) [0.02] 1 (1.43) [0.13] 12.5 9.1

1] 75 (83.40) [0.85] 7 (8.19) [0.17] 67 63.6

34 (21.96) [6.61] 2 (2.16) [0.01] 30.4 18.2

3 (6.64) [2.00] 2 (0.65) [2.78] 2.6 18.2

554 A.A. Rabaan et al. / Journal of Infection and Public Health 10 (2017) 548–563

Table 6 Distribution of responses by age group.

Question Response All staff (N = 607) 18–29 (N = 179) 30–44 (N = 305) 45–59 (N = 112) ≥60 (N = 11) p Number/percentage of group

Question 1a Y 500/82.37 140/78.2 246/80.7 103/92.0 11/100 0. 003737 N 55/9.06 14/7.8 36/11.8 5/4.5 0/0 DK 52/8.57 25/14.0 23/7.5 4/3.5 0/0

Question 1b Y 486/80.07 140/78.2 238/78.0 97/86.6 11/100 0.254737 N 82/13.51 26/14.5 44/14.4 12/10.7 0/0 DK 39/6.43 13/7.3 23/7.5 3/2.7 0/0

Question 2 Y 467/76.94 134/74.9 235/77.0 90/80.4 8/72.7 0.732612 N 140/23.06 45/25.1 70/23.0 22/19.6 3/27.3

Question 3 Y 389/64.09 97/54.2 198/64.9 85/75.9 9/81.8 0.001612 N 144/23.72 51/28.5 68/22.3 24/21.4 1/9.1 DK 74/12.19 31/17.3 39/12.8 3/2.7 1/9.1

Question 4 Y 242/39.87 61/34.1 113/37.0 62/55.4 6/54.5 0.000993 N 170/28.01 44/24.6 95/31.2 28/25.0 3/27.3 DK 195/32.13 74/41.3 97/31.8 22/19.6 2/18.2

Question 5 Y 272/44.81 74/41.3 137/44.9 55/49.1 6/54.5 0.00503 N 218/35.91 54/30.2 113/37.1 47/42.0 4/36.4 DK 117/19.28 51/28.5 55/18.0 10/8.9 1/9.1

Question 6 Y 269/44.15 64/35.8 138/45.2 60/53.6 7/63.6 0. 000631 N 125/20.76 31/17.3 64/21.0 29/25.9 1/9.1 DK 213/35.09 84/46.9 103/33.8 23/20.5 3/27.3

Question 7 Y 285/46.95 74/41.3 137/44.9 66/58.9 8/72.7 0.029958 N 206/33.94 64/35.8 107/35.1 32/28.6 3/27.3 DK 116/19.11 41/22.9 61/20.0 14/12.5 0/0

Question 8 Healthcare associated 129/21.25 32/17.9 67/22.0 24/21.4 5/45.4 0.009744 All 282/46.46 74/41.3 141/46.2 64/57.2 3/27.3 DK 196/32.29 73/40.8 97/31.8 24/21.4 3/27.3

Question 9 Y 313/51.57 74/41.3 164/53.8 68/60.7 7/63.6 0.006374 N 118/19.44 34/19.0 61/20.0 22/19.6 1/9.1 DK 176/28.99 71/39.7 80/26.2 22/19.6 3/27.3

Question 10 Y 296/48.76 83/46.4 144/53.8 62/34.6 7/63.6 0.130947 N 217/35.75 62/34.6 114/37.4 40/35.7 1/9.1 DK 94/15.49 34/19.0 47/15.4 10/8.9 3/27.3

Question 11 Y 316/52.06 75/41.9 167/54.8 68/60.7 6/54.5 0.004331 N 156/25.70 48/26.8 74/24.3 30/26.8 4/36.4 DK 135/22.24 56/31.3 64/20.9 14/12.5 1/9.1

Question 12 Y 196/32.29 50/27.9 106/34.8 36/32.1 4/36.4 0.78509 N 329/54.01 104/58.1 161/52.8 59/52.7 5/45.4 DK 82/13.51 25/14.0 38/12.4 17/15.2 2/18.2

.8

.2

.0

i t q t p t y l A f t i p b s a a o

Question 13 Y 194/31.96 57/31 N 314/51.73 88/49 DK 99/16.31 34/19

For the questions relating to readiness and competence of the nstitution and staff (Questions 10–13, Section “Subjects and ques- ionnaires”), there was significant variation with age group for uestion 11 (whether the surveillance tool used in their institu- ion is effective to prevent or control infection; Chi square 18.9028;

= 0.004331). Once again, this was mainly attributable to higher han expected levels of ‘don’t know’ answers among the 18–29 ears category, while respondents in the 45–59 year category had ower than expected levels of ‘don’t know’ responses (Table 6, ppendix D). For question 10 (whether their hospital is prepared

or any infection outbreak; Chi square 9.8538, p = 0.130947), ques- ion 12 (whether all staff in their unit were following promptly nfection control policies, rules and guidelines; Chi square 3.1866;

= 0.78509) and question 13 (whether all staff can differentiate etween different isolation protocols such as droplet or contact; Chi quare 8.0098; p = 0.237384), there was no significant difference in

ge group distribution (Table 6, Appendix D). This was reflective of

relatively uniform level of pessimism (‘No’ responses) regardless f age group in response to these questions.

92/30.2 39/34.8 6/54.5 0.237384 161/52.8 62/55.4 3/27.3 52/17.0 11/9.8 2/18.2

In terms of nationality, we considered whether there were any differences in responses between Saudi and non-Saudi staff. There was a significant difference in distribution of Saudi versus non- Saudi staff by institution type (Chi square 85.6424; p < 0.00001; Table 7). This was mainly due to non-Saudi staff being significantly more likely than expected to work in private hospitals or poly clin- ics, and significantly less likely to work in government hospitals, while the opposite was the case for Saudi staff (Table 7). By con- trast, there was no significant variation in Saudi and non-Saudi staff among the different HCW professions (Chi square 4.8523; p = 0.18294).

There was some variation in responses between Saudi and non- Saudi staff (Table 8, Appendix E). Numbers and percentages of responses in each group and the p value obtained from Chi square analyses are shown in Table 6 and the Chi square breakdowns are shown in Appendix E.

There was variation in responses to questions related to institution-specific issues (Questions 1–5, Section “Subjects and questionnaires”). For knowing whether or not there is an infec- tion control program at their institution (Question 1a), there was

A.A. Rabaan et al. / Journal of Infection and Public Health 10 (2017) 548–563 555

Table 7 Institution distribution by nationality.

Type of institution

Government hospital Private hospital Poly clinic (n/%) N (expected) [Chi square] N (expected) [Chi square] N (expected) [Chi square] % of national group % of national group % of national group

Saudi (n = 446) 376 (332.11) [5.80] 54 (87.44) [12.79] 16 (26.45) [4.13] 84.30 12.11 4.44

Non-Saudi (n = 161) 76 (119.89) [16.07] 65 (31.56) [35.42] 20 (9.55) [11.44] 47.20 40.37 12.42

Table 8 Distribution of responses by nationality.

Question Response All staff (n = 607) Saudi (n = 446) Non-Saudi (n = 161) p

Number/percentage of groups Question 1a Y 500/82.37 362/81.17 138/85.71 0.429242

N 55/9.06 43/9.64 12/7.45 DK 52/8.57 41/9.19 11/6.83

Question 1b Y 486/80.07 346/77.58 142/88.20 0.006838 N 82/13.51 70/15.70 10/6.21 DK 39/6.43 30/6.73 9/5.59

Question 2 Y 467/76.94 333/74.66 134/83.23 0.026984 N 140/23.06 113/25.34 27/16.77

Question 3 Y 389/64.09 267/59.87 122/75.78 0.000354 N 144/23.72 113/25.34 31/19.25 DK 74/12.19 66/14.80 8/4.97

Question 4 Y 242/39.87 156/34.98 86/53.42 0.000036 N 170/28.01 127/28.48 43/26.71 DK 195/32.13 163/36.55 32/19.88

Question 5 Y 273/44.98 198/44.39 74/45.96 0.002252 N 217/35.75 148/33.18 70/43.48 DK 117/19.28 100/22.42 17/10.56

Question 6 Y 269/44.15 177/39.69 92/57.14 0.000019 N 125/20.76 89/19.96 36/22.36 DK 213/35.09 180/40.36 33/20.50

Question 7 Y 285/46.95 189/42.38 96/59.63 0.000697 N 206/33.94 162/36.32 44/27.33 DK 116/19.11 95/21.30 21/13.04

Question 8 Healthcare associated 129/21.25 90/20.18 38/23.60 0.033835 All 282/46.46 198/44.39 84/52.17 DK 196/32.29 158/35.43 39/24.22

Question 9 Y 313/51.57 205/45.96 108/67.08 <0.00001 N 118/19.44 89/19.96 29/18.01 DK 176/28.99 152/34.08 24/14.91

Question 10 Y 296/48.76 193/43.27 103/63.98 <0.00001 N 217/35.75 183/41.03 34/21.1 DK 94/15.49 70/15.70 24/14.91

Question 11 Y 316/52.06 217/48.65 99/61.49 0.012195 N 156/25.70 119/26.68 37/22.98 DK 135/22.24 110/24.66 25/15.53

Question 12 Y 196/32.29 125/28.03 71/44.10 0.000642 N 329/54.01 260/58.30 69/42.86 DK 82/13.51 61/13.68 21/13.04

Question 13 Y 194/31.96 119/26.68 75/46.58 0.000021 N 314/51.73 248/55.61 66/40.99

Y pariso

n 1 r t d n I o

DK 99/16.31

: yes; N: no; DK: don’t know; p < 0.05 considered significant (from Chi square com

o significant difference noted across the groups (Chi square .6915; p = 0.429242). However, there was significant variation in esponses as to whether there is an infection control program in heir unit (Question 1b; Chi square 9.9706; p = 0.006838), mainly

ue to higher than expected numbers of Saudi staff responding egatively, while the opposite was the case for non-Saudi staff.

n terms of whether staff had received some form of training or rientation about infection prevention and control, there was also

79/17.71 20/12.42

n).

significant variation (Question 2; Chi square 4.8919; p = 0.026984; Table 8, Appendix E). This was mainly due to lower than expected numbers of non-Saudi staff responding negatively. There were also significantly different levels of awareness of whether there is an

active infection control team in their institution (Question 3; Chi square 15.8924; p = 0.000354), mainly attributable to non-Saudi staff being more likely than expected to respond positively and less likely to respond negatively or with a ‘don’t know’ answer. The

5 ion an

d ( v h b A l ‘ e t t r w A

6 c v i p o t c l ‘ A r a w r h i t w l w

i t b 2 Q s w r w f

C

t c b a t a h b t f f 6 s t l

56 A.A. Rabaan et al. / Journal of Infect

istribution was similar to that obtained for private hospital staff Tables 3 and 8, Appendices C and E). There was also significant ariation in responses to the question of whether the institution ad an emerging infectious diseases task force (dealing with out- reaks) (Chi square 20.4543; p = 0.000036; Question 4; Table 8, ppendix E). This was mainly due to non-Saudi staff being more

ikely than expected to respond positively, and less likely to respond don’t know. On the question of whether an outbreak had ever been ncountered in their institution, there was also significant varia- ion (Question 5; Chi square 12.1919; p = 0.002252), mainly due o non-Saudi staff being significantly less likely than expected to espond negatively or with a ‘don’t know’ answer, while Saudi staff ere more likely than expected to respond ‘don’t know’ (Table 8, ppendix E).

On questions on surveillance and reporting standards (questions –9, Section “Subjects and questionnaires”), there was also signifi- ant variability in responses to all questions. There was significant ariation on the question of whether their hospital is enrolled n national surveillance system (Question 6; Chi square 21.7659;

= 0.000019; Table 8, Appendix E), and on whether there was a list f reportable infectious agents available in their unit and accessible o all staff (Question 7; Chi square 14.5375; p = 0.000697). In both ases, this was mainly attributable to non-Saudi staff being more ikely than expected to respond positively and less likely to respond don’t know’, while the opposite was true for Saudi staff. (Table 8, ppendix E). With respect to the question of which infections are eported to the MOH (Question 8), there was also significant vari- tion (Chi square 6.7725; p = 0.033835; Table 8, Appendix E). This as mainly due to non-Saudi staff being relatively less likely to

espond ‘don’t know’. On the question of whether their institution ad a known turnaround time of laboratory results of the reportable

nfectious agents (Question 9), there was again significant varia- ion (Chi square 25.4586; p < 0.00001; Table 8, Appendix E). This as mainly attributable to non-Saudi staff being significantly more

ikely to respond positively and significantly less likely to respond ith a ‘don’t know’ answer, similar to private hospital staff.

On questions relating to readiness and competence of the nstitution and staff (Questions 10–13, Section “Subjects and ques- ionnaires”), there also variability in responses to all questions etween staff of different nationalities (Question 10: Chi square 3.5655, p < 0.00001; Question 11: Chi square 8.8135, p = 0.012195; uestion 12: Chi square 14.7013, p = 0.000642; Question 13: Chi

quare 21.5735, p = 0.000021; Table 8, Appendix E). In all cases, this as again due to non-Saudi staff being significantly more likely to

espond positively and less likely to respond either negatively or ith a ‘don’t know’ than expected, while the opposite was the case

or Saudi staff.

auses, contributing factors and surveillance/reporting systems

The staff were asked to identify what they considered to be he cause(s) of outbreaks from a list of choices (Table 9). The top ited overall cause was carelessness of healthcare workers (cited y 395 HCW, 65.07% of the total group). This was the case across ll three institution types. They were also asked to identify fac- ors that contribute to the spread of infection in the hospital from

series of choices. The top-cited factor by the group overall was ospital infrastructure and design (329; 54.20%), followed closely y lack and shortage of staff (326; 53.71%) and no infection control raining program (314; 51.73%) (Table 9). When considered for dif- erent institution types, lack and shortage of staff was the top cited actor within both government and private hospitals (53.8% and

5.6% respectively), while this was cited by only 13.9% of poly clinics taff. In poly clinics, the top-cited cause it was no infection control raining program (20; 55.6%). Staff were also asked what surveil- ance/reporting systems were used in their institutions, and which

d Public Health 10 (2017) 548–563

surveillance/reporting system they would consider most effective (Table 9). The most widely used was a paper version (395; 65.07%), but this was the least frequently chosen option by participants (197/32.45%). An electronic surveillance system was the least often used (312; 51.40%), but considered the most effective by the high- est number of staff (493; 81.22%). An electronic surveillance system was reported as the most commonly used only in private hospitals (81.51% compared to 43.58% of government hospitals and 50.00% of poly clinics).

Discussion

The aim of this study was to assess awareness of, and adher- ence to, infection prevention and control guidelines and policies among HCWs in healthcare institutions in Saudi Arabia, including government hospitals, private hospitals and poly clinics. Responses to a series of questions on infection prevention and control were assessed from the perspectives of different HCW professions, insti- tution types, participant age groups and Saudi versus non-Saudi staff.

Saudi Arabia faces unique public health challenges, for exam- ple the Umrah and Haji pilgrimages attract more than seven million pilgrims to Saudi Arabia from nearly 200 countries [21]. Infection prevention and control policies at both national macro- policy and at institution and departmental micro-policy level must reflect these challenges. In all cases, training of staff and effective communication of specific guidelines, policies and procedures are imperative in ensuring implementation. Responses in our study suggested relatively high levels of uncertainty among HCWs on per- sonnel and institution-specific issues, surveillance and reporting standards, and readiness and competence to implement poli- cies and respond to outbreaks. There was evidence of variability between different HCW professions, institution types, age groups, and between Saudi versus non-Saudi staff. Evidence emerged, for example, that many staff were unaware of availability of informa- tion on reportable infections in their own units, did not feel they had sufficient training and were not confident that infection control guidelines and procedures were being implemented by colleagues. Staff in private hospitals expressed more confidence than those in government hospitals on a number of issues. Differences between Saudi and non-Saudi staff may reflect the fact that non-Saudi staff were more likely than Saudi staff to work in private hospitals.

There have been a number of infection outbreaks in Saudi Ara- bia in recent years, most significantly Middle East Respiratory Syndrome (MERS) [5–8]. Most outbreaks have occurred in govern- ment hospitals, consistent with the results of our study suggesting greater confidence and preparedness of staff in private hospitals compared to government hospitals. The largest hospital-associated outbreak occurred in a government hospital in Jeddah in 2014, in which illness spread among both hospital patients and HCWs [5,9,11,12]. Other government hospital-based clusters of MERS- CoV cases occurred in Riyadh in 2014 and 2015 [5,22]. A World Health Organization (WHO) investigation revealed issues such as overcrowding in emergency department waiting rooms, and incon- sistent application of basic infection control procedures, such as hand hygiene and use of personal protective equipment (PPE), as factors in MERS-CoV outbreaks in hospitals in Saudi Arabia [11]. In the Jeddah hospital, aggressive improvement in infection control deficiencies resulted in a decline in cases [18]. The MOH introduced new infection prevention and control guidelines for MERS-CoV patients [6,13–16]. Many of these guidelines are generally appli- cable to infection prevention and control for all infectious diseases,

with emphasis on standard, contact, droplet and airborne precau- tions, management of overcrowding, and triaging in the emergency department [6]. The MOH expressed the hope that they would be strictly adhered to by all HCWs and in all healthcare facilities [6].

A.A. Rabaan et al. / Journal of Infection and Public Health 10 (2017) 548–563 557

Table 9 Causes, contributing factors and surveillance system effectiveness.

Number/percentage of total

In your opinion, what is the cause(s) of outbreaks: Breaching infection control policies, rules, and guidelines 308/50.74 No clear infection control policies, rules, and guidelines 229/37.73 Carelessness of healthcare workers 395/65.07 (top cited cause)) Shortage of appropriate personnel protective equipment 259/42.67 Infection control infrastructures do not exist 207/34.10

Factors that contribute to the spread of infection in the hospital: Hospital infrastructure and design 329/54.20 (top cited factor) Lack and shortage of staff 326/53.71 No infection control training program 314/51.73 No resources to fulfil the infection control requirements and needs 264/43.49 No infection control on-call 199/32.78

Reporting system Used in institution? (number/percentage) Most effective? (number/percentage)

d c a N t n i t n s t a a i f t

s p s o i i t C p s t p t p

b m a [ m r H t e e s i t

Electronic surveillance system 312/51.40 Paper version 395/65.07 Telephone communication 280/46.13

Despite this, in our study the majority of staff of all professions id not think staff in their unit were following promptly infection ontrol policies, rules and guidelines, or that all staff can differenti- te between different isolation protocols such as droplet or contact. urses generally tended to have more confidence and be less uncer-

ain than the other professions on these and other questions. While urses were more likely to be female than male, gender had no

mpact on responses to any of the questions asked, thus the varia- ion in nurses’ responses did not relate to gender. Physicians were otably more pessimistic than other staff on these points. While taff in private hospitals were more likely to think that staff in heir unit were following promptly infection control policies, rules nd guidelines, nevertheless positive responses were confined to

minority of staff, and there was no significant difference across nstitution types on whether staff can differentiate between dif- erent isolation protocols such as droplet or contact. Effective staff raining on these elements appears to be urgently required.

A majority of staff of all types and across all institutions reported ome experience of training or orientation, with nurses and staff in rivate hospitals most likely to have received training. Despite this, taff also identified lack of an infection control training program as ne of the most important factors that contribute to the spread of nfection in the hospital. This suggests that the level of staff training s not considered adequate by HCWs to equip them for implemen- ation of infection control and prevention policy and guidelines. onsistent with this, there was a low level of confidence in the reparedness of institutions for any infection outbreak, although taff in private hospitals and nurses in general were more posi- ive. Staff perceive that government hospitals and poly clinics in articular need urgently to address staff training and orientation o ensure effective implementation of MOH guidelines and ensure reparedness for any infection outbreak.

The effectiveness of promotion and consistent application of oth basic infection control procedures, such as hand hygiene, and ore advanced measures, has been demonstrated in the hospital-

ssociated MERS-CoV outbreaks in Saudi Arabia and in Korea 17–20]. A combination of advanced and basic infection control

easures also reduced transmission of MERS-CoV to HCWs in a ecent study in a tertiary care institution in Saudi Arabia [17]. owever, for effective implementation of MOH-prescribed infec-

ion control and prevention measures, consultation of front-line mployees is vital, and expectations of both management and

mployees should be clearly defined, communicated and under- tood [1,7]. Understaffing, frequent staff turnover, poor design and nfrastructure of facilities and lack of education and training oppor- unities are factors that can impact on effective infection prevention

493/81.22 197/32.45 259/42.67

and control [23]. Consistent with this, in our study staff identified hospital infrastructure and design, lack and shortage of staff and no infection control training program as the top factors contributing to the spread of infection in the hospital. Participants perceived that carelessness of healthcare workers was the main cause of outbreaks. Although this perception may be faulty, the pressures imposed on staff by inadequate nurse/physician to patient ratios, lack of adequate system resources and sub-optimal hospital infras- tructure can challenge the ability of staff to consistently and carefully apply infection prevention and control procedures. Fur- thermore, there was a relatively high level of uncertainty among some staff types, notably physicians and staff in poly clinics, as to existence of infection control policies and guidelines in their unit. This suggests a breakdown in communication of expecta- tions and guidelines. This could contribute to apparent carelessness in application of procedures, as staff are unclear as to what the required procedures are. There was also a strikingly high lack of uncertainty among staff of all HCW professions as to whether their institution had an emerging infectious diseases task force (deal- ing with outbreaks), and indeed as to whether their institution has ever experienced an outbreak. Uncertainty on these questions was particularly striking among younger staff, suggesting that further training and communication with HCWs in the 18–29 year old age group across all professions would be beneficial.

MOH-prescribed infection control and prevention measures include advice and directions on enrolment of hospitals in the national surveillance system and the reporting of infectious agents to the MOH. There was a strikingly high lack of certainty among staff of all types and across institutions as to whether their hos- pital was enrolled in the national surveillance system. There was also high uncertainty as to what infections should be reported, with nurses and staff at private hospitals being less uncertain than other staff. Again, younger staff were significantly less certain than staff aged over 45 years old. Lack of certainty on this point may relate to lack of availability of, access to, or awareness of, a list of reportable infectious agents available within units. In either case, this suggests an urgent need to meet staff needs for access to such lists, which would be relatively easily addressed.

Overall, disappointingly low numbers of staff of all types thought that the surveillance tool used in their institution was effective to prevent or control infection, even in private hospi- tals, an element that could be relatively easily addressed. The

most commonly used tool–except for in private hospitals–was a paper version, but this was considered least effective by staff. An electronic surveillance system was the least often used–except in private hospitals–but considered the most effective by staff. Imple-

5 ion an

m m h

c e t w S s o H t i i n I s s t t w A b t o

p c b n w r a n a c a t c

i c f w t o t o

A

v

A

reportable infectious agents: Yes

58 A.A. Rabaan et al. / Journal of Infect

entation of electronic surveillance systems would therefore be a easure that could be implemented more widely in government

ospitals and poly clinics to improve staff confidence. Effectiveness of adherence to effective infection control pro-

edures has been demonstrated in hospitals in Saudi Arabia. For xample, increased compliance with hand hygiene practices due o a series of interventions over a five year period was associated ith reduction in HC-MRSA and device-associated infections in a

audi hospital [24]. Also, a suite of advanced infection control mea- ures in addition to basic IC measures resulted in no transmission f MERS-CoV to HCWs [17]. The results of our study suggest that CWs in Saudi Arabia are aware of limitations in infection con-

rol and prevention implementation, and of exacerbating factors n their institutions. Multiple steps are needed to facilitate staff in mplementation of guidelines and policies and to improve aware- ess and compliance, for example on hand hygiene compliance in

CU units [7]. Thus, as evident from the responses of staff in our tudy, the approach to infection prevention and control measures hould be multi-factorial and include ongoing provision of educa- ion and training, prominent reminders and reliable provision of he materials needed to implement the policies and guidelines, as ell as the involvement and support of hospital management [7]. ttention should also be paid to differences in emphases that may e required in different vulnerable units or departments, including he emergency department, inpatient areas, the dialysis unit and utpatient areas [18,23,25].

While our study has given some insights into the knowledge and erception of HCWs in Saudi Arabia in infection prevention and ontrol in their institutions, it has some limitations. The method y which the questionnaire was administered meant that we had o information as to the number of institutions the respondents ere gathered from. Nor could we check whether the ‘yes’ and ‘no’

esponses were ‘correct’ for particular institutions, as we did not sk respondents for the identity of their institutions. The question- aire also did not allow participants to elaborate on elements such s the level or type of training they received or what they would lass as ‘carelessness’ in implementation of infection prevention nd control measures. Participants also chose to respond, and might herefore be more than averagely motivated individuals rather than ompletely representative of the HCW population as a whole.

In conclusion, we have identified areas of concern among HCWs n healthcare facilities in Saudi Arabia on infection prevention and ontrol, which vary between institutions and among different pro- essions. These issues merit urgent action in terms consultation ith and training of staff, improvement of communication of infec-

ion prevention and control guidelines and policies, and provision f adequate resources and equipment, to improve implementa- ion of infection prevention and control policies and try to ensure utbreaks such as MERS-CoV can be minimized and contained.

cknowledgment

The authors would like to thank all the participants in this sur- ey.

ppendix A. : Study questionnaire

Age: 18–24 25–30 31–40 41–50 51–60 >60

Gender: Male Female

d Public Health 10 (2017) 548–563

Medical Profession: Physician Nursing Lab Tech Others

I am working at: Private hospital Government hospital Poly clinic (private sector)

Do you have infection control program at your institution? Yes No Don’t know

Have you received some form of training or orientation about infection prevention and control?

Yes No

Do you have infection control policies and guidelines in your unit? Yes No Don’t know

Do you think that all staff in your unit are following promptly infection control policies, rules and guidelines?

Yes No Don’t know

Do you think your hospital is prepared for any infection outbreak? Yes No Don’t know

In your opinion, what is the cause(s) of outbreaks? Breaching infection control policies, rules, and guidelines No clear infection control policies, rules, and guidelines Carelessness of healthcare workers Shortage of appropriate personnel protective equipment Infection control infrastructures do not exist

Factors that contribute to the spread of infection in the hospital: Hospital infrastructure and design Lack and shortage of staff No infection control training program No resources to fulfill the infection control requirements and needs No infection control on-call

At your institution, do you have active infection control team? Yes No Don’t know

Do you think that all staff can differentiate between different isolation protocol such as droplet or contact?

Yes No Don’t know

Do you have a list of reportable infectious agents available in your unit and accessible to all staff:

Yes No Don’t know

Is your hospital is enrolled in national surveillance system: Yes No Don’t know

Which infections are reported to MOH: All healthcare associated infections All infections (both hospital and community acquired) Don’t know

In your institution, is there known turnaround time of laboratory results of the

No Don’t know

ion and Public Health 10 (2017) 548–563 559

A

Nurses Lab staff Others

136 (133.44) [0.05] 191 (191.93) [0.00] 57 (65.07) [1.00] 15 (14.68) [0.01] 23 (21.11) [0.17] 9 (7.16) [0.47] 11 (13.88) [0.60] 19 (19.96) [0.05] 13 (6.77) [5.74]

142 (129.71) [1.17] 191 (186.55) [0.11] 54 (63.25) [1.35] 16 (21.88) [1.58] 31 (31.48) [0.01] 14 (10.67) [1.04] 4 (10.41) [3.95] 11 (14.97) [1.05] 11 (5.08) [6.91]

142 (124.64) [2.42] 165 (179.26) [1.13] 58 (60.78) [0.13] 20 (37.36) [8.07] 68 (53.74) [3.78] 21 (18.22) [0.42]

116 (103.82) [1.43] 143 (149.32) [0.27] 53 (50.63) [0.11] 31 (38.43) [1.44] 57 (55.28) [0.05] 13 (18.74) [1.76] 15 (19.75) [1.14] 33 (28.41) [0.74] 13 (9.63) [1.18]

73 (64.59) [1.10] 87 (92.89) [0.37] 33 (31.50) [0.07] 44 (45.37) [0.04] 63 (65.26) [0.08] 21 (22.13) [0.06] 45 (52.04) [0.95] 83 (74.85) [0.89] 25 (25.38) [0.01]

82 (72.59) [1.22] 84 (104.41) [3.99] 36 (35.40) [0.01] 46 (58.18) [2.55] 99 (83.68) [2.80] 25 (28.37) [0.40] 34 (31.23) [0.25] 50 (44.91) [0.58] 18 (15.23) [0.50]

84 (71.79) [2.08] 89 (103.26) [1.97] 36 (35.01) [0.03] 27 (33.36) [1.21] 54 (47.98) [0.75] 18 (16.27) [0.18] 51 (56.85) [0.60] 90 (81.76) [0.83] 25 (27.72) [0.27]

84 (71.79) [2.08] 89 (103.26) [1.97] 36 (35.01) [0.03] 27 (33.36) [1.21] 54 (47.98) [0.75] 18 (16.27) [0.18] 51 (56.85) [0.60] 90 (81.76) [0.83] 25 (27.72) [0.27]

84 (71.79) [2.08] 89 (103.26) [1.97] 36 (35.01) [0.03] 27 (33.36) [1.21] 54 (47.98) [0.75] 18 (16.27) [0.18] 51 (56.85) [0.60] 90 (81.76) [0.83] 25 (27.72) [0.27]

82 (83.54) [0.03] 146 (120.15) [5.56] 35 (40.74) [0.81] 27 (31.49) [0.64] 48 (45.29) [0.16] 13 (15.36) [0.36] 53 (46.97) [0.77] 39 (67.56) [12.07] 31 (22.91) [2.86]

95 (79.00) [3.24] 107 (113.62) [0.39] 44 (38.52) [0.78] 56 (57.91) [0.06] 79 (83.30) [0.22] 20 (28.24) [2.41] 11 (25.09) [7.91] 47 (36.08) [3.30] 15 (12.23) [0.63]

91 (84.34) [0.53] 128 (121.30) [0.37] 43 (41.13) [0.09] 37 (41.63) [0.52] 59 (59.88) [0.01] 17 (20.30) [0.54] 34 (36.03) [0.11] 46 (51.82) [0.65] 19 (17.57) [0.12]

55 (52.31) [0.14] 82 (75.24) [0.61] 31 (25.51) [1.18] 95 (87.81) [0.59] 121 (126.29) [0.22] 34 (42.82) [1.82] 12 (21.88) [4.46] 30 (31.48) [0.07] 14 (10.67) [1.04]

A.A. Rabaan et al. / Journal of Infect

What is reporting system do you have at your hospitals: Electronic surveillance system Paper version Telephone communication

In your opinion, what is the effective reporting system for reporting infectious agents:

Electronic surveillance system Paper version Telephone communication

Do you have an emerging infectious diseases task force (dealing with outbreaks)

Yes No Don’t know

Do you agree that surveillance tool used in your institution is effective to prevent or control infection

Yes No Don’t know

ppendix B. : Chi square breakdown profession type

Profession

Question Response Physicians N (Expected) [Chi square]

1a Y 116 (109.6) [0.38] N 8 (12.05) [1.36] DK 9 (11.39) [0.50]

1b Y 99 (106.49) [0.53] N 21 (17.97) [0.51] DK 13 (8.55) [2.32]

2 Y 102(102.32)[0.00] N 31 (30.68) [0.00]

3 Y 77 (85.23) [0.80] N 43 (31.55) [4.15] DK 13 (16.21) [0.64]

4 Y 49 (53.02) [0.31] N 42 (37.25) [0.61] DK 42 (42.73) [0.01]

5 Y 70 (59.60) [1.82] N 48 (47.77) [0.00] DK 15 (25.64) [4.41]

6 Y 60 (58.94) [0.02] N 26 (27.39) [0.07] DK 47 (46.67) [0.00]

7 Y 60 (58.94) [0.02] N 26 (27.39) [0.07] DK 47 (46.67) [0.00]

8 Healthcare 60 (58.94) [0.02] All 26 (27.39) [0.07] DK 47 (46.67) [0.00]

9 Y 50 (68.58) [5.03] N 30 (25.86) [0.66] DK 53 (38.56) [5.40]

10 Y 50 (64.86) [3.40] N 62 (47.55) [4.39] DK 21 (20.60) [0.01]

11 Y 54 (69.24) [3.35] N 43 (34.18) [2.28] DK 36 (29.58) [1.39]

12 Y 28 (42.95) [5.20] N 79 (72.09) [0.66] DK 26 (17.97) [3.59]

13 Y 28 (42.51) [4.95] 77 (5 N 88 (68.80) [5.36] 69 (8 DK 17 (21.69) [1.01] 16 (2

Y: yes; N: No; DK: Don’t know.

1.78) [12.29] 64 (74.47) [1.47] 25 (25.25) [0.00] 3.80) [2.61] 124 (120.53) [0.10] 33 (40.87) [1.51] 6.42) [4.11] 45 (38.00) [1.29] 21 (12.88) [5.11]

5 ion and Public Health 10 (2017) 548–563

A

spital Private hospital Poly clinic

0] 108 (98.02) [1.02] 19 (29.65) [3.83] ] 5 (10.78) [3.10] 9 (3.26) [10.09] ] 6 (10.19) [1.73] 8 (3.08)[7.84]

9] 113 (95.28) [3.30] 23 (28.82) [1.18] ] 4 (16.08) [9.07] 8 (4.86) [2.02] ] 2 (7.65) [4.17] 5 (2.31) [3.12]

7] 102 (91.55) [1.19] 25 (27.70) [0.26] 8] 17 (27.45) [3.98] 11 (8.30) [0.88]

9] 96 (76.26) [5.11] 14 (23.07) [3.57] 3] 14 (28.23) [7.17] 19 (8.54) [12.81] ] 9 (14.51) [2.09] 3 (4.39) [0.44]

.12] 64 (47.44) [5.78] 12 (14.35) [0.39]

.23] 25 (33.33) [2.08] 13 (10.08) [0.84]

.53] 30 (38.23) [1.77] 11 (11.57) [0.03]

.03] 55 (53.32) [0.05] 12 (16.13) [1.06]

.54] 45 (42.74) [0.12] 20 (12.93) [3.87] ] 19 (22.94) [0.68] 4 (6.94) [1.24]

.53] 66 (52.74) [3.34] 13 (15.95) [0.55] ] 23 (24.51) [0.09] 9 (7.41) [0.34] .68] 30 (41.76) [3.31] 14 (12.63) [0.15]

.32] 66 (55.87) [1.84] 15 (16.90) [0.21]

.60] 32 (40.39) [1.74] 11 (12.22) [0.12] ] 21 (22.74) [0.13] 10 (6.88) [1.42]

4] 17 (25.09) [2.61] 10 (7.59) [0.76] .68] 73 (55.29) [5.68] 11 (16.72) [1.96] .27] 29 (38.62) [2.40] 15 (11.68) [0.94]

.49] 87 (61.36) [10.71] 17 (18.56) [0.13] ] 14 (23.13) [3.61] 9 (7.00) [0.57] .19] 18 (34.50) [7.89] 10 (10.44) [0.02]

.17] 86 (58.03) [13.48] 16 (17.56) [0.14]

.00] 18 (42.54) [14.16] 12 (12.87) [0.06] ] 15 (18.43) [0.64] 8 (5.57) [1.05]

.29] 73 (61.95) [1.97] 16 (18.74) [0.40]

.53] 23 (30.58) [1.88] 9 (9.25) [0.01]

.00] 23 (26.47) [0.45] 11 (8.01) [1.12]

.53] 51 (38.43) [4.12] 14 (11.62) [0.49]

.32] 54 (64.50) [1.71] 12 (19.51) [2.89] ] 14 (16.08) [0.27] 10 (4.86) [5.43]

60 A.A. Rabaan et al. / Journal of Infect

ppendix C. : Chi square breakdown institution type

Institution

Question Response Government ho N (Expected) [Chi square]

1a Y 373 (372.3) [0.0 N 41 (40.96) [0.00 DK 38 (38.72) [0.01

1b Y 350 (361.9) [0.3 N 70 (61.06) [1.31 DK 32 (29.04) [0.30

2 Y 340 (347.8) [0.1 N 112 (104.3) [0.5

3 Y 279 (289.7) [0.3 N 111 (107.2) [0.1 DK 62 (55.10) [0.86

4 Y 166 (180.20) [1 N 132 (126.59) [0 DK 154 (145.21) [0

5 Y 205 (202.54) [0 N 153 (162.33) [0 DK 94 (87.12) [0.54

6 Y 190 (200.31) [0 N 93 (93.08) [0.00 DK 169 (158.61) [0

7 Y 204 (212.22) [0 N 163 (153.40) [0 DK 85 (86.38) [0.02

8 Healthcare 101 (95.31) [0.3 All 198 (209.99) [0 DK 153 (146.70) [0

9 Y 209 (233.07) [2 N 95 (87.87) [0.58 DK 148 (131.06) [2

10 Y 194 (220.42) [3 N 187 (161.59) [4 DK 71 (70.00) [0.01

11 Y 227 (235.31) [0 N 124 (116.16) [0 DK 101 (100.53) [0

12 Y 131 (145.95) [1 N 263 (244.99) [1 DK 58 (61.06) [0.15

13 Y 134 (144.46) [0.76] N 245 (233.82) [0.53] DK 73 (73.72) [0.01]

Y: yes; N: No; DK: Don’t know.

48 (38.03) [2.61] 12 (11.51) [0.02] 52 (61.56) [1.48] 17 (18.62) [0.14] 19 (19.41) [0.01] 7 (5.87) [0.22]

ion and Public Health 10 (2017) 548–563 561

A

30–44 45–59 ≥60

246 (251.24) [0.11] 103 (92.26) [1.25] 11 (9.06) [0.41] 36 (27.64) [2.53] 5 (10.15) [2.61] 0 (1.00) [1.00] 23 (26.13) [0.37] 4 (9.59) [3.26] 0 (0.94) [0.94]

238 (244.20) [0.16] 97 (89.67) [0.60] 11 (8.81) [0.55] 44 (41.20) [0.19] 12 (15.13) [0.65] 0 (1.49) [1.49] 23 (19.60) [0.59] 3 (7.20) [2.45] 0 (0.71) [0.71]

235 (234.65) [0.00] 90 (86.17) [0.17] 8 (8.46) [0.03] 70 (70.35) [0.00] 22 (25.83) [0.57] 3 (2.54) [0.08]

198 (195.46) [0.03] 85 (71.78) [2.44] 9 (7.05) [0.54] 68 (72.36) [0.26] 24 (26.57) [0.25] 1 (2.61) [0.99] 39 (37.18) [0.09] 3 (13.65) [8.31] 1 (1.34) [0.09]

113 (121.60) [0.61] 62 (44.65) [6.74] 6 (4.39) [0.59] 95 (85.42) [1.07] 28 (31.37) [0.36] 3 (3.08) [0.00] 97 (97.98) [0.01] 22 (35.98) [5.43] 2 (3.53) [0.67]

137 (136.67) [0.00] 55 (50.19) [0.46] 6 (4.93) [0.23] 113 (109.54) [0.11] 47 (40.22) [1.14] 4 (3.95) [0.00] 55 (58.79) [0.24] 10 (21.59) [6.22] 1 (2.12) [0.59]

138 (135.16) [0.06] 60 (49.63) [2.16] 7 (4.87) [0.93] 64 (62.81) [0.02] 29 (23.06) [1.53] 1 (2.27) [0.71] 103 (107.03) [0.15] 23 (39.30) [6.76] 3 (3.86) [0.19]

137 (143.20) [0.27] 66 (52.59) [3.42] 8 (5.16) [1.56] 107 (103.51) [0.12] 32 (38.01) [0.95] 3 (3.73) [0.14] 61 (58.29) [0.13] 14 (21.40) [2.56] 0 (2.10) [2.10]

67 (64.32) [0.11] 24 (23.62) [0.01] 5 (2.32) [3.10] 141 (141.70) [0.00] 64 (52.03) [2.75] 3 (5.11) [0.87] 97 (98.99) [0.04] 24 (36.35) [4.20] 3 (3.57) [0.09]

164 (157.27) [0.29] 68 (57.75) [1.82] 7 (5.67) [0.31] 61 (59.29) [0.05] 22 (21.77) [0.00] 1 (2.14) [0.61] 80 (88.43) [0.80] 22 (32.47) [3.38] 3 (3.19) [0.01]

144 (148.73) [0.15] 62 (54.62) [1.00] 7 (5.36) [0.50] 114 (109.04) [0.23] 40 (40.04) [0.00] 1 (3.93) [2.19] 47 (47.23) [0.00] 10 (17.34) [3.11] 3 (1.70) [0.99]

167 (158.78) [0.43] 68 (58.31) [1.61] 6 (5.73) [0.01] 74 (78.39) [0.25] 30 (28.78) [0.05] 4 (2.83) [0.49] 64 (67.83) [0.22] 14 (24.91) [4.78] 1 (2.45) [0.86]

106 (98.48) [0.57] 36 (36.16) [0.00] 4 (3.55) [0.06] 161 (165.31) [0.11] 59 (60.71) [0.05] 5 (5.96) [0.16]

A.A. Rabaan et al. / Journal of Infect

ppendix D. : Chi square breakdown age group

Age group

Question Response 18–29 N (Expected) [Chi square]

1a Y 140 (147.45) [0.38] N 14 (16.22) [0.30] DK 25 (15.33) [6.09]

1b Y 140 (143.32) [0.08] N 26 (24.18) [0.14] DK 13 (11.50) [0.20]

2 Y 134 (137.71) [0.10] N 45 (41.29) [0.33]

3 Y 97 (114.71) [2.74] N 51 (42.46) [1.72] DK 31 (21.82) [3.86]

4 Y 61 (71.36) [1.51] N 44 (50.13) [0.75] DK 74 (57.50) [4.73]

5 Y 74 (80.21) [0.48] N 54 (64.29) [1.65] DK 51 (34.50) [7.89]

6 Y 64 (79.33) [2.96] N 31 (36.86) [0.93] DK 84 (62.81) [7.15]

7 Y 74 (84.04) [1.20] N 64 (60.75) [0.17] DK 41 (34.21) [1.35]

8 Healthcare 32 (37.75) [0.87] All 74 (83.16) [1.01] DK 73 (58.09) [3.82]

9 Y 74 (92.30) [3.63] N 34 (34.80) [0.02] DK 71 (51.90) [7.03]

10 Y 83 (87.29) [0.21] N 62 (63.99) [0.06] DK 34 (27.72) [1.42]

11 Y 75 (93.19) [3.55] N 48 (46.00) [0.09] DK 56 (39.81) [6.58]

12 Y 50 (57.80) [1.05] N 104 (97.02) [0.50]

DK 25 (24.18) [0.03] 38

13 Y 57 (57.21)[0.00] 92 N 88 (92.60) [0.23] 16 DK 34 (29.19) [0.79] 52

(41.20) [0.25] 17 (15.13) [0.23] 2 (1.49) [0.18]

(97.48) [0.31] 39 (35.80) [0.29] 6 (3.52) [1.76] 1 (157.78) [0.07] 62 (57.94) [0.28] 3 (5.69) [1.27]

(49.74) [0.10] 11 (18.27) [2.89] 2 (1.79) [0.02]

5 ion and Public Health 10 (2017) 548–563

A

i Non-Saudi

367.38) [0.08] 138 (132.62) [0.22] 0.41) [0.17] 12 (14.59) [0.46] 8.21) [0.20] 11 (13.79) [0.57]

358.56) [0.44] 142 (129.44) [1.22] 8.78) [2.14] 10 (21.22) [5.93] 8.66) [0.06] 9 (10.34) [0.17]

343.13) [0.30] 134 (123.87) [0.83] 102.87) [1.00] 27 (37.13) [2.77]

285.82) [1.24] 122 (103.18) [3.43] 105.81) [0.49] 31 (38.19) [1.36] 4.37) [2.49] 8 (19.63) [6.89]

177.81) [2.68] 86 (64.19) [7.41] 124.91) [0.03] 43 (45.09) [0.10] 143.28) [2.71] 32 (51.72) [7.52]

199.86) [0.02] 74 (72.14) [0.05] 160.18) [0.93] 70 (57.82) [2.56] 85.97) [2.29] 17 (31.03) [6.35]

197.65) [2.16] 92 (71.35) [5.98] 1.85) [0.09] 36 (33.15) [0.24] 156.50) [3.53] 33 (56.50) [9.77]

209.41) [1.99] 96 (75.59) [5.51] 151.36) [0.75] 44 (54.64) [2.07] 5.23) [1.12] 21 (30.77) [3.10]

4.05) [0.17] 38 (33.95) [0.48] 207.20) [0.41] 84 (74.80) [1.13] 144.75) [1.21] 39 (52.25) [3.36]

229.98) [2.71] 108 (83.02) [7.52] 6.70) [0.06] 29 (31.30) [0.17] 129.32) [3.98] 24 (46.68) [11.02]

217.49) [2.76] 103 (78.51) [7.64] 159.44) [3.48] 34 (57.56) [9.64] 9.07) [0.01] 24 (24.93) [0.03]

232.18) [0.99] 99 (83.82) [2.75] 114.62) [0.17] 37 (41.38) [0.46] 99.19) [1.18] 25 (35.81) [3.26]

144.01) [2.51] 71 (51.99) [6.95] 241.74) [1.38] 69 (87.26) [3.82] 0.25) [0.01] 21 (21.75) [0.03]

142.54) [3.89] 75 (51.46) [10.77] 230.71) [1.29] 66 (83.29) [3.59] 2.74) [0.54] 20 (26.26) [1.49]

R

[

[ [

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62 A.A. Rabaan et al. / Journal of Infect

ppendix E. : Chi square breakdown nationality

Nationality

Question Response Saud N (Expected) [Chi square]

1a Y 362 ( N 43 (4 DK 41 (3

1b Y 346 ( N 70 (5 DK 30 (2

2 Y 333 ( N 113 (

3 Y 267 ( N 113 ( DK 66 (5

4 Y 156 ( N 127 ( DK 163 (

5 Y 198 ( N 148 ( DK 100 (

6 Y 177 ( N 89 (9 DK 180 (

7 Y 189 ( N 162 ( DK 95 (8

8 Healthcare 90 (9 All 198 ( DK 158 (

9 Y 205 ( N 89 (8 DK 152 (

10 Y 193 ( N 183 ( DK 70 (6

11 Y 217 ( N 119 ( DK 110 (

12 Y 125 ( N 260 ( DK 61 (6

13 Y 119 ( N 248 ( DK 79 (7

Y: yes; N: No; DK: Don’t know.

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